Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

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Showing developments with attributable Research & technical analysis reactions.

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Building & implementation Research & technical analysis
1 live reaction map in this view Jump to the evidence ↓
Multiple readings Inference Cooperative — AI, governed together Building & implementation · 2 attributable reactions
Most important

The developments commanding sustained expert attention

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

New Culture, work & education Development 5h ago
AI education meta-analyses audit finds flaws

39 meta-analyses, 39 positive findings: An audit finds serious flaws in research on AI in education

4 experts across 3 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · Ben Williamson
“The research record on AI in education is already pretty appalling. And researchers just keep cranking up AI to do yet more meta-reviews that then recycle the findings of sloppy studies like this one. hechingerreport.org/proof-points...” evidence ↗
4 experts 3 communities 1 sources clustered
Mar Hicks Hypervisible Luke Stark Ben Williamson

“The research record on AI in education is already pretty appalling. And researchers just keep cranking up AI to do yet more meta-reviews that then recycle the findings of sloppy studies like this one. hechingerreport.org/proof-points...”

Primary source hechingerreport.org ↗
Developing Policy & governance Resource 1d ago
⚡ 153 h early
inference cooperative AI governance

Inference Cooperative — AI, governed together

3 experts across 3 network communities independently surfaced this.

Why this matches Research & technical analysis reaction 2 attributable expert contributions · Nathan Schneider, B! 🐝 Cavello (they/them)
“There are now hand-made doodles on the Inference Cooperative home page. It's a small, superficial thing, but to me it matters: To make clear that the heart of this co-op is the people who join, not the AI tools we share. https://inference.coop” evidence ↗
3 experts 3 communities 1 sources clustered
Ronen Tamari Nathan Schneider B! 🐝 Cavello (they/them)
How the network is reacting Experts are approaching this through 2 distinct lenses.
Multiple readings

Building & implementation

1 expert

How teams are shipping and applying it.

“Maybe relevant @ntnsndr.in in context of inference.coop (congrats on the launch!)”

Research & technical analysis

1 expert

Evidence, methods and technical implications.

“There are now hand-made doodles on the Inference Cooperative home page. It's a small, superficial thing, but to me it matters: To make clear that the heart of this co-op is the people who join, not the AI tools we share. https://inference.coop”

2 experts discussed this · 6 posts
Nathan Schneider: A month ago, I found myself in the unexpected position of founding an AI startup. Today, the Inference Co-op adopted its first real governance charter. We can't make AI good, but we can own our cho…
B! 🐝 Cavello (they/them): A month ago, I found myself in the unexpected position of founding an AI startup. Today, the Inference Co-op adopted its first real governance charter. We can't make AI good, but we can own our cho…
Marco Z: where does it run ? is that Tinfoil?
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Primary source inference.coop ↗
New Agents & robotics Research 23h ago
advantage clipped policy optimization RL paper

Towards Better Training Signal: Advantage Clipped Policy Optimization

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · AI Firehose
“Researchers introduced Advantage Clipped Policy Optimization (ACPO), a method that stabilizes gradient estimates via clipping. This innovation boosts training efficiency and accuracy for language models in reasoning tasks, yielding significant gains on benc…” evidence ↗
1 expert 1 community 1 sources clustered
AI Firehose

“Researchers introduced Advantage Clipped Policy Optimization (ACPO), a method that stabilizes gradient estimates via clipping. This innovation boosts training efficiency and accuracy for language models in reasoning tasks, yielding significant gains on benc…”

Primary source arxiv.org ↗
Developing Policy & governance Research 1d ago
policy rubric co-evolution generation paper

Co-Evolving Policy and Rubric via Capability Awareness for Open-Ended Generation

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · AI Firehose
“CoCA adapts reinforcement learning for large language models, co-evolving policy and rubric based on capability awareness, enhancing performance in open-ended generation tasks. This ensures evaluation criteria evolve with model capabilities for safer AI int…” evidence ↗
1 expert 1 community 1 sources clustered
AI Firehose

“CoCA adapts reinforcement learning for large language models, co-evolving policy and rubric based on capability awareness, enhancing performance in open-ended generation tasks. This ensures evaluation criteria evolve with model capabilities for safer AI int…”

Primary source arxiv.org ↗
Developing Policy & governance Research 1d ago
weakening self-distillation reasoning paper

Weaken to Strengthen: Weakening-Induced On-Policy Self-Distillation for Large Reasoning Models

1 directory member surfaced this signal.

Why this matches Research & technical analysis reaction 1 attributable expert contribution · AI Firehose
“This study presents Weakening-Induced On-Policy Self-Distillation (WISD), enhancing reasoning models' accuracy by up to 5.5 points without privileged data. Using weaker model contrasts through quantization and pruning, WISD redefines self-distillation for A…” evidence ↗
1 expert 1 community 1 sources clustered
AI Firehose

“This study presents Weakening-Induced On-Policy Self-Distillation (WISD), enhancing reasoning models' accuracy by up to 5.5 points without privileged data. Using weaker model contrasts through quantization and pruning, WISD redefines self-distillation for A…”

Primary source arxiv.org ↗
Debates gaining attention

What experts are discussing without an anchoring article

4 experts · 8 posts · 1d ago
Ted Underwood Eli Sennesh tweety fish Singularity's Bounty e/cc
Matches Research & technical analysis
“whatever secret training software engineers are receiving that allows them to evaluate—and change—previous opinions, it's really something we should consider trying on academics” evidence ↗
Multiple readings Markets & investment · 1 Research & technical analysis · 1
Ted Underwood: whatever secret training software engineers are receiving that allows them to evaluate—and change—previous opinions, it's really something we should consider trying on academics
Ted Underwood: it's just very notable that a lot of explicitly AI-skeptical engineers performed a kind of transformation over the last twelve months where they almost "changed," so to speak, "their mind" — though…
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